Machine Learning Engineer

Java, Python, R, ETL, Data management, Scala, SQL, SAS, Analytics, Apache Hadoop, Apache Kafka, TensorFlow, Keras, scikit-learn, Big data, Data science, Predictive analytics, Machine learning, Apache Spark, Data analysis, IBM, RDBMS, Predictive modelling, Artificial intelligence
Full Time
$80,800+
Work from home not available Travel not required

Job Description

The Machine Learning Engineer is responsible for designing, developing, optimizing, testing and deploying machine learning to support experimentation and innovation to help build cutting edge artificial intelligence solutions for the Enterprise. Incumbent must be adept about exploring and visualizing data to understand its quality and identifying differences that could affect performance when deploying the model.

 

Principal Responsibilities

  • Performs data preparation, formatting and feature engineering activities using large scale data sets (greater than 10GB) in preparation for machine learning and predictive modeling.
  • Researches coding methods to achieve desired data transformations, while ensuring data transformations are meaningful to model discovery.
  • Develop machine learning pipelines and applications that interact with algorithms utilizing open-source toolsets. 
  • Serves as a resource for cross-functional data teams to assist with coding and business requests.
  • Collaborates with data team to deliver meaningful insights into the model discovery workflows, providing training to others on data preparation and lineage, and developing efficient data transformations as the needs of the model and data team dictate.
  • Other duties as assigned

 

Education & Experience:

 

1. Must meet one of the following:

  • Bachelor’s degree and six  (6) years experience
  • Master’s degree and four (4) years experience

 

Field of study: math, science, statistics, economics, finance, informatics, computer science, information systems, health information, epidemiology, data analytics, data science, predictive analytics, artificial intelligence, engineering, physics or related fields.

Knowledge of open-source application stack commonly used in data science workflows (Pandas, Spark, Sci-kit Learn, TensorFlow, Keras)

 

Experience: analytics, high-level programming, predictive modeling, relational databases, big data, open-source software, feature engineering, data transformation, ETL, API development, data processing, statistical analysis, data exploration.

 

2. Certifications preferred:  Designated certification may be used in lieu of some experience i.e.  Coursera IBM Data Science, Data Engineering with GCP, IBM Applied AI, or IBM Applied Engineering.  

3. Specialized training in Data Engineering, Data Science, Machine Learning, Big Data Platforms (Spark, Kafka, Hadoop, H2O, etc.), High Level Programming in Data Engineering, Data Science, or Machine Learning (Python, Scala, Java, R, SAS for Data Science, etc).

 

Specialized Knowledge & Skills

  • Ability to work independently
  • Critical thinking and decision making
  • Good written and oral communication
  • Familiarity with machine learning concepts
  • Professionalism
  • Collaboration
  • Ability to meet deadlines
  • Multitasking
  • Delegating and monitoring
  • Expert SQL knowledge
  • Data management toolsets
  • High-level programming language (Python, R, Scala, Java, C++, SAS etc.)
  • ETL programming

 

Preferred Skills:

  • Knowledge of open-source application stack commonly used in data science workflows (Pandas, Spark, Sci-kit Learn, TensorFlow, Keras)
  • Parallelized computing
  • Feature engineering
  • Healthcare knowledge
  • API development
  • Data transformation of unstructured or semi-structured data
  • Machine Learning Data Pipelines
Dice Id : 10453405
Position Id : R0004194
Originally Posted : 2 weeks ago
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